{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T18:08:17Z","timestamp":1778782097120,"version":"3.51.4"},"reference-count":72,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFC3106302"],"award-info":[{"award-number":["2022YFC3106302"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62161010"],"award-info":[{"award-number":["62161010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62361024"],"award-info":[{"award-number":["62361024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42476201"],"award-info":[{"award-number":["42476201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.engappai.2026.114637","type":"journal-article","created":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T16:08:43Z","timestamp":1775059723000},"page":"114637","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Diffusion model-enhanced coral identification: A lightweight multi-scale network for benthic imagery analysis"],"prefix":"10.1016","volume":"175","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-8246-6575","authenticated-orcid":false,"given":"Changen","family":"Yang","sequence":"first","affiliation":[]},{"given":"Zhi","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6837-9024","authenticated-orcid":false,"given":"Zhuhua","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Zhaoxuan","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Yijun","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Xi","family":"Liang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"4","key":"10.1016\/j.engappai.2026.114637_b1","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1007\/s10462-025-11116-x","article-title":"Advances in diffusion models for image data augmentation: A review of methods, models, evaluation metrics and future research directions","volume":"58","author":"Alimisis","year":"2025","journal-title":"Artif. Intell. Rev."},{"issue":"13","key":"10.1016\/j.engappai.2026.114637_b2","doi-asserted-by":"crossref","first-page":"5117","DOI":"10.1021\/acs.est.2c05369","article-title":"Toward a new era of coral reef monitoring","volume":"57","author":"Apprill","year":"2023","journal-title":"Environ. Sci. Technol."},{"issue":"7","key":"10.1016\/j.engappai.2026.114637_b3","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0130312","article-title":"Towards automated annotation of benthic survey images: Variability of human experts and operational modes of automation","volume":"10","author":"Beijbom","year":"2015","journal-title":"PLoS ONE"},{"key":"10.1016\/j.engappai.2026.114637_b4","series-title":"Large scale GAN training for high fidelity natural image synthesis","author":"Brock","year":"2018"},{"key":"10.1016\/j.engappai.2026.114637_b5","series-title":"A comprehensive survey of AI-generated content (AIGC): A history of generative AI from GAN to ChatGPT","author":"Cao","year":"2023"},{"issue":"7","key":"10.1016\/j.engappai.2026.114637_b6","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s10462-024-10788-1","article-title":"Dynamic YOLO for small underwater object detection","volume":"57","author":"Chen","year":"2024","journal-title":"Artif. Intell. Rev."},{"key":"10.1016\/j.engappai.2026.114637_b7","article-title":"Discrete edge feature guided rotation detection method for remote sensing ship wake","author":"Chen","year":"2025","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"10.1016\/j.engappai.2026.114637_b8","doi-asserted-by":"crossref","DOI":"10.1109\/TIM.2020.3040485","article-title":"RetinaNet with difference channel attention and adaptively spatial feature fusion for steel surface defect detection","volume":"70","author":"Cheng","year":"2021","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.engappai.2026.114637_b9","first-page":"8780","article-title":"Diffusion models beat GANs on image synthesis","volume":"Vol. 34","author":"Dhariwal","year":"2021"},{"issue":"1","key":"10.1016\/j.engappai.2026.114637_b10","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-024-79211-7","article-title":"Lightweight enhanced YOLOv8n underwater object detection network for low light environments","volume":"14","author":"Ding","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.engappai.2026.114637_b11","doi-asserted-by":"crossref","unstructured":"Ding, X., Zhang, X., Han, J., Ding, G., 2022. Scaling up your kernels to 31x31: Revisiting large kernel design in CNNs. In: Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.. CVPR, pp. 11953\u201311965.","DOI":"10.1109\/CVPR52688.2022.01166"},{"key":"10.1016\/j.engappai.2026.114637_b12","doi-asserted-by":"crossref","first-page":"11886","DOI":"10.1109\/JSTARS.2024.3419786","article-title":"A small-ship object detection method for satellite remote sensing data","volume":"17","author":"Fan","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"issue":"4","key":"10.1016\/j.engappai.2026.114637_b13","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.cub.2014.12.022","article-title":"Species richness on coral reefs and the pursuit of convergent global estimates","volume":"25","author":"Fisher","year":"2015","journal-title":"Curr. Biol."},{"key":"10.1016\/j.engappai.2026.114637_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecoinf.2021.101527","article-title":"A novel feature descriptor based coral image classification using extreme learning machine with ameliorated chimp optimization algorithm","volume":"68","author":"Ganesan","year":"2022","journal-title":"Ecol. Inf."},{"key":"10.1016\/j.engappai.2026.114637_b15","series-title":"YOLOX: Exceeding YOLO series in 2021","author":"Ge","year":"2021"},{"issue":"3","key":"10.1016\/j.engappai.2026.114637_b16","doi-asserted-by":"crossref","first-page":"489","DOI":"10.3390\/rs12030489","article-title":"Monitoring of coral reefs using artificial intelligence: A feasible and cost-effective approach","volume":"12","author":"Gonzalez-Rivero","year":"2020","journal-title":"Remote. Sens."},{"issue":"12","key":"10.1016\/j.engappai.2026.114637_b17","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1109\/TPAMI.2010.168","article-title":"Single image haze removal using dark channel prior","volume":"33","author":"He","year":"2011","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.engappai.2026.114637_b18","series-title":"Denoising diffusion probabilistic models","first-page":"6840","volume":"Vol. 33","author":"Ho","year":"2020"},{"key":"10.1016\/j.engappai.2026.114637_b19","doi-asserted-by":"crossref","unstructured":"Hu, Z., Li, X., Xie, X., Zhao, Y., 2022. Abnormal behavior recognition of underwater fish body based on C3D model. In: Proc. 6th Int. Conf. Mach. Learn. Soft Comput.. pp. 92\u201397.","DOI":"10.1145\/3523150.3523165"},{"key":"10.1016\/j.engappai.2026.114637_b20","series-title":"Proc. Int. Conf. Learn. Represent.","article-title":"LoRA: Low-rank adaptation of large language models","author":"Hu","year":"2022"},{"issue":"11","key":"10.1016\/j.engappai.2026.114637_b21","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1016\/j.tree.2010.07.011","article-title":"Rising to the challenge of sustaining coral reef resilience","volume":"25","author":"Hughes","year":"2010","journal-title":"Trends Ecol. Evol."},{"issue":"7645","key":"10.1016\/j.engappai.2026.114637_b22","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1038\/nature21707","article-title":"Global warming and recurrent mass bleaching of corals","volume":"543","author":"Hughes","year":"2017","journal-title":"Nature"},{"key":"10.1016\/j.engappai.2026.114637_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2020.116088","article-title":"Underwater image processing and analysis: A review","volume":"91","author":"Jian","year":"2021","journal-title":"Signal Process., Image Commun."},{"key":"10.1016\/j.engappai.2026.114637_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.marenvres.2023.106157","article-title":"Coral detection, ranging, and assessment (CDRA) algorithm-based automatic estimation of coral reef coverage","volume":"191","author":"Jiang","year":"2023","journal-title":"Mar. Environ. Res."},{"issue":"9","key":"10.1016\/j.engappai.2026.114637_b25","doi-asserted-by":"crossref","DOI":"10.3390\/s24092905","article-title":"YOLOv8-MU: An improved YOLOv8 underwater detector based on a large kernel block and a multi-branch reparameterization module","volume":"24","author":"Jiang","year":"2024","journal-title":"Sensors"},{"key":"10.1016\/j.engappai.2026.114637_b26","series-title":"YOLOv5 by ultralytics","author":"Jocher","year":"2023"},{"key":"10.1016\/j.engappai.2026.114637_b27","series-title":"YOLOv8 by ultralytics","author":"Jocher","year":"2023"},{"key":"10.1016\/j.engappai.2026.114637_b28","series-title":"YOLOv11: An overview of the key architectural enhancements","author":"Khanam","year":"2024"},{"issue":"1","key":"10.1016\/j.engappai.2026.114637_b29","doi-asserted-by":"crossref","first-page":"151","DOI":"10.5334\/aogh.2831","article-title":"Human health and ocean pollution","volume":"86","author":"Landrigan","year":"2020","journal-title":"Ann. Glob. Health"},{"key":"10.1016\/j.engappai.2026.114637_b30","series-title":"YOLOv13: Real-time object detection with hypergraph-enhanced adaptive visual perception","author":"Lei","year":"2025"},{"key":"10.1016\/j.engappai.2026.114637_b31","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2019.107038","article-title":"Underwater scene prior inspired deep underwater image and video enhancement","volume":"98","author":"Li","year":"2020","journal-title":"Pattern Recognit."},{"issue":"12","key":"10.1016\/j.engappai.2026.114637_b32","doi-asserted-by":"crossref","first-page":"5664","DOI":"10.1109\/TIP.2016.2612882","article-title":"Underwater image enhancement by dehazing with minimum information loss and histogram distribution prior","volume":"26","author":"Li","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.engappai.2026.114637_b33","doi-asserted-by":"crossref","first-page":"4376","DOI":"10.1109\/TIP.2019.2955241","article-title":"An underwater image enhancement benchmark dataset and beyond","volume":"29","author":"Li","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.engappai.2026.114637_b34","series-title":"YOLOv6: A single-stage object detection framework for industrial applications","author":"Li","year":"2022"},{"issue":"3","key":"10.1016\/j.engappai.2026.114637_b35","doi-asserted-by":"crossref","DOI":"10.1007\/s11554-024-01436-6","article-title":"Slim-neck by GSConv: A lightweight-design for real-time detector architectures","volume":"21","author":"Li","year":"2024","journal-title":"J. Real-Time Image Process."},{"key":"10.1016\/j.engappai.2026.114637_b36","doi-asserted-by":"crossref","unstructured":"Li, B., Peng, X., Wang, Z., et al., 2017. AOD-Net: All-in-one dehazing network. In: Proc. IEEE Int. Conf. Comput. Vis.. ICCV, pp. 4770\u20134778.","DOI":"10.1109\/ICCV.2017.511"},{"key":"10.1016\/j.engappai.2026.114637_b37","series-title":"Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection","author":"Li","year":"2020"},{"key":"10.1016\/j.engappai.2026.114637_b38","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecoinf.2023.102261","article-title":"Applying deep learning to predict SST variation and tropical cyclone patterns that influence coral bleaching","volume":"77","author":"Lin","year":"2023","journal-title":"Ecol. Inf."},{"key":"10.1016\/j.engappai.2026.114637_b39","doi-asserted-by":"crossref","unstructured":"Liu, C.W., Li, H.J., Wang, S.C., et al., 2021. A dataset and benchmark of underwater object detection for robot picking. In: Proc. IEEE Int. Conf. Multimed. Expo. ICME.","DOI":"10.1109\/ICMEW53276.2021.9455997"},{"key":"10.1016\/j.engappai.2026.114637_b40","doi-asserted-by":"crossref","unstructured":"Lu, X., Li, B., Yue, Y., et al., 2019. Grid R-CNN. In: Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.. CVPR, pp. 7355\u20137364.","DOI":"10.1109\/CVPR.2019.00754"},{"key":"10.1016\/j.engappai.2026.114637_b41","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecoinf.2024.102937","article-title":"SCoralDet: Efficient real-time underwater soft coral detection with YOLO","volume":"85","author":"Lu","year":"2025","journal-title":"Ecol. Inf."},{"key":"10.1016\/j.engappai.2026.114637_b42","series-title":"Are GANs created equal? A large-scale study","volume":"Vol. 31","author":"Lucic","year":"2018"},{"issue":"1","key":"10.1016\/j.engappai.2026.114637_b43","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-024-66950-w","article-title":"Underwater small target detection under YOLOv8-LA model","volume":"14","author":"Qu","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.engappai.2026.114637_b44","series-title":"Proc. Int. Conf. Mach. Learn.","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021"},{"key":"10.1016\/j.engappai.2026.114637_b45","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A., 2016. You only look once: Unified, real-time object detection. In: Proc. IEEE Conf. Comput. Vis. Pattern Recognit.. CVPR, pp. 779\u2013788.","DOI":"10.1109\/CVPR.2016.91"},{"issue":"6","key":"10.1016\/j.engappai.2026.114637_b46","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.engappai.2026.114637_b47","series-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.","first-page":"22500","article-title":"DreamBooth: Fine tuning text-to-image diffusion models for subject-driven generation","author":"Ruiz","year":"2023"},{"issue":"2","key":"10.1016\/j.engappai.2026.114637_b48","doi-asserted-by":"crossref","DOI":"10.3390\/rs17020185","article-title":"Understanding the influence of image enhancement on underwater object detection: A quantitative and qualitative study","volume":"17","author":"Saleem","year":"2025","journal-title":"Remote. Sens."},{"issue":"1","key":"10.1016\/j.engappai.2026.114637_b49","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-024-73243-9","article-title":"UICE-mirnet guided image enhancement for underwater object detection","volume":"14","author":"Sarkar","year":"2024","journal-title":"Sci. Rep."},{"issue":"2","key":"10.1016\/j.engappai.2026.114637_b50","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1007\/s11263-019-01228-7","article-title":"Grad-CAM: Visual explanations from deep networks via gradient-based localization","volume":"128","author":"Selvaraju","year":"2020","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.engappai.2026.114637_b51","series-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2015"},{"key":"10.1016\/j.engappai.2026.114637_b52","series-title":"Status of Coral Reefs of the World: 2020 Report","year":"2021"},{"key":"10.1016\/j.engappai.2026.114637_b53","series-title":"Status of Coral Reefs of the World: 2025 Report","year":"2025"},{"key":"10.1016\/j.engappai.2026.114637_b54","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., et al., 2016. Rethinking the Inception architecture for computer vision. In: Proc. IEEE Conf. Comput. Vis. Pattern Recognit.. CVPR, pp. 2818\u20132826.","DOI":"10.1109\/CVPR.2016.308"},{"key":"10.1016\/j.engappai.2026.114637_b55","doi-asserted-by":"crossref","unstructured":"Tian, Z., Shen, C., Chen, H., He, T., 2019. FCOS: Fully convolutional one-stage object detection. In: Proc. IEEE\/CVF Int. Conf. Comput. Vis.. ICCV, pp. 9626\u20139635.","DOI":"10.1109\/ICCV.2019.00972"},{"key":"10.1016\/j.engappai.2026.114637_b56","series-title":"YOLOv12: Attention-centric real-time object detectors","author":"Tian","year":"2025"},{"key":"10.1016\/j.engappai.2026.114637_b57","series-title":"Wise-iou: Bounding box regression loss with dynamic focusing mechanism","author":"Tong","year":"2023"},{"key":"10.1016\/j.engappai.2026.114637_b58","article-title":"Attention is all you need","volume":"Vol. 30","author":"Vaswani","year":"2017"},{"key":"10.1016\/j.engappai.2026.114637_b59","series-title":"YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","author":"Wang","year":"2022"},{"key":"10.1016\/j.engappai.2026.114637_b60","series-title":"YOLOv10: Real-time end-to-end object detection","author":"Wang","year":"2024"},{"key":"10.1016\/j.engappai.2026.114637_b61","series-title":"YH-MINER: Multimodal intelligent system for natural ecological reef metric extraction","author":"Wang","year":"2025"},{"key":"10.1016\/j.engappai.2026.114637_b62","series-title":"YOLOv9: Learning what you want to learn using programmable gradient information","author":"Wang","year":"2024"},{"key":"10.1016\/j.engappai.2026.114637_b63","series-title":"AI-generated content (AIGC): A survey","author":"Wu","year":"2023"},{"key":"10.1016\/j.engappai.2026.114637_b64","doi-asserted-by":"crossref","DOI":"10.1016\/j.marenvres.2024.106644","article-title":"Improved research on coral bleaching detection model based on FCOS model","volume":"200","author":"Xin","year":"2024","journal-title":"Mar. Environ. Res."},{"key":"10.1016\/j.engappai.2026.114637_b65","doi-asserted-by":"crossref","unstructured":"Yang, Z., Liu, S., Hu, H., et al., 2019. RepPoints: Point set representation for object detection. In: Proc. IEEE\/CVF Int. Conf. Comput. Vis.. ICCV, pp. 9656\u20139665.","DOI":"10.1109\/ICCV.2019.00975"},{"issue":"11","key":"10.1016\/j.engappai.2026.114637_b66","doi-asserted-by":"crossref","first-page":"6129","DOI":"10.1109\/TNNLS.2021.3072414","article-title":"Lightweight deep neural network for joint learning of underwater object detection and color conversion","volume":"33","author":"Yeh","year":"2022","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"4","key":"10.1016\/j.engappai.2026.114637_b67","first-page":"523","article-title":"Segmentation and measurement scheme for fish morphological features based on mask R-CNN","volume":"7","author":"Yu","year":"2020","journal-title":"Inf. Process. Agric."},{"key":"10.1016\/j.engappai.2026.114637_b68","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.107506","article-title":"An intelligent measurement scheme for basic characters of fish in smart aquaculture","volume":"204","author":"Yu","year":"2023","journal-title":"Comput. Electron. Agric."},{"issue":"18","key":"10.1016\/j.engappai.2026.114637_b69","doi-asserted-by":"crossref","first-page":"3555","DOI":"10.3390\/rs13183555","article-title":"Real-time underwater maritime object detection in side-scan sonar images based on transformer-YOLOv5","volume":"13","author":"Yu","year":"2021","journal-title":"Remote. Sens."},{"key":"10.1016\/j.engappai.2026.114637_b70","series-title":"Proc. IEEE\/CVF Winter Conf. Appl. Comput. Vis.","first-page":"767","article-title":"CNet: A novel seabed coral reef image segmentation approach based on deep learning","author":"Zhang","year":"2024"},{"key":"10.1016\/j.engappai.2026.114637_b71","series-title":"Proc. IEEE\/CVF Int. Conf. Comput. Vis.","first-page":"3836","article-title":"Adding conditional control to text-to-image diffusion models","author":"Zhang","year":"2023"},{"key":"10.1016\/j.engappai.2026.114637_b72","series-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit.","first-page":"28170","article-title":"CoralSCOP: Segment any coral image on this planet","author":"Zheng","year":"2024"}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095219762600919X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095219762600919X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T17:11:40Z","timestamp":1778778700000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S095219762600919X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":72,"alternative-id":["S095219762600919X"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114637","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Diffusion model-enhanced coral identification: A lightweight multi-scale network for benthic imagery analysis","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114637","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114637"}}